A dedicated intelligent fusion terminal guide rail modular installation system and method

Abstract

The application relates to the field of power equipment installation, and discloses a smart terminal rail modular installation system and method, which dynamically senses the installation state of a terminal body, generates an initial constraint model of the installation direction in combination with a posture angle detection result, performs direction deviation detection on the initial constraint model, calculates a longitudinal and transverse posture offset, pushes an extension module into a standardized interface of the terminal body along a rail direction, and monitors a pushing angle and contact pressure in real time during plugging; when it is detected that the pushing angle deviates from a preset range and is accompanied by abnormal contact pressure change, whether the pushing angle adjustment is accompanied by correction of the pressure distribution is judged; if the pressure cannot be restored to normal after the angle adjustment, a pressure auxiliary adjustment strategy is started in the pushing angle correction process; after the pushing angle and the contact pressure are both returned to a balanced state, adaptive pushing stable control is performed; and the application has the advantages of improving installation and maintenance efficiency.

Description

Technical Field

[0001] This invention relates to the field of power equipment installation, specifically to a modular installation system and method for a dedicated transformer intelligent integrated terminal rail. Background Technology

[0002] With the continuous advancement of digital and intelligent transformation of power distribution networks, smart integrated terminals for dedicated transformers are increasingly being widely used on the power user side. Their modular, rail-mounted installation method has become the mainstream solution for functional expansion and standardized assembly. Existing rail-mounted modular installation technologies primarily focus on the general interface definition of module units, the mechanical strength of rail clips, and the safety of electrical connections. However, some minor and easily overlooked issues still exist in specific application scenarios. For example, in the distribution rooms of renovated old urban residential areas, cabinet space is limited and wiring is complex. When construction workers quickly replace or temporarily expand smart integrated terminal modules in confined spaces, slight misalignment often occurs during the insertion of the rail and module due to positioning deviations. This prevents the module from sliding in smoothly in one go, leading to uneven local stress on the connector, incomplete locking of clips, and even poor contact of the grounding spring. Although this problem is a minor detail, it can easily cause module communication interruptions, protection function failures, or grounding hazards in actual operation, increasing the frequency and risk of maintenance for operation and maintenance personnel. Therefore, it is essential to design a rail-mounted modular installation system and method for smart integrated terminals for dedicated transformers that improves installation and maintenance efficiency. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a modular installation system and method for intelligent integrated terminal rails of special transformers, which has the advantage of improving installation and maintenance efficiency and solves the problems mentioned in the background technology.

[0004] To achieve the aforementioned goal of improving installation and maintenance efficiency, this invention provides the following technical solution: a modular installation method for a dedicated transformer intelligent fusion terminal rail, comprising the following steps:

[0005] The installation status of the terminal body is dynamically sensed, and the sliding direction of the terminal body is intelligently mapped based on the hierarchical limiting structure of the guide rail slot. The initial constraint model of the installation direction is generated by combining the attitude angle detection results.

[0006] The initial constraint model is subjected to directional deviation detection. The longitudinal and lateral attitude offsets are calculated by combining the spatial difference between the guide protrusion in the guide rail slot and the main body attitude vector. The initial constraint model is then adaptively corrected based on the offsets.

[0007] The expansion module is pushed into the standardized interface of the terminal body along the guide rail direction. The symmetrical guiding structure of the interface and the differentiated distribution of contact points are used to establish the constraint relationship in the guide rail direction. The pushing angle and contact pressure are monitored in real time during the insertion process.

[0008] When the propulsion angle deviates from the preset range and is accompanied by abnormal changes in contact pressure, the angle and pressure joint correction mechanism is activated to analyze the coupling relationship between the abnormal angle and the abnormal pressure, and to determine whether the adjustment of the propulsion angle will lead to the correction of the pressure distribution. If the pressure cannot be restored to normal after the angle adjustment, the pressure auxiliary adjustment strategy will be activated simultaneously during the propulsion angle correction process.

[0009] After the propulsion angle and contact pressure have returned to equilibrium, adaptive propulsion stabilization control is implemented.

[0010] Preferably, the process of generating the initial constraint model for the installation direction based on the attitude angle detection results is as follows:

[0011] Using multi-axis attitude sensors in the installation environment, the spatial position, tilt angle, yaw angle and pitch angle of the terminal body are collected synchronously;

[0012] Based on the geometric reference plane of the guide rail slot, the angle distribution between the central axis of the terminal body and the reference axis of the slot is calculated, and the attitude angle vector field is generated.

[0013] A weighted fitting algorithm is used to perform multidimensional constraint fusion on the attitude angle vector field and extract the weight factors of the offset in each direction;

[0014] The weighting factors are input into the initial constraint modeling unit, and the initial constraint model for the installation direction is generated by combining the deformation estimation results of the terminal body shell with the installation space boundary conditions.

[0015] Preferably, the process for calculating the longitudinal and lateral attitude offsets is as follows:

[0016] The attitude angle information of the terminal body in the guide rail slot coordinate system is extracted from the initial constraint model, and a mapping function between lateral offset and longitudinal offset is established.

[0017] Real-time offset data during the sliding process is collected by micro-displacement sensors deployed on both sides of the guide rail and compared with the attitude angle predicted trajectory;

[0018] A two-way differential compensation algorithm is used to eliminate sensor drift error and obtain the corrected real-time offset.

[0019] Based on the hierarchical characteristics of the guide rail slot limit boundary, calculate the joint offset vector of longitudinal and lateral offsets, and output the attitude offset.

[0020] Preferably, the process of adaptively correcting the initial constraint model based on the offset is as follows:

[0021] By combining the attitude offset with the real-time pressure distribution at the guide rail contact point and the groove deformation state, the constraint surface position adjustment parameters are dynamically calculated.

[0022] Using a gradient descent-based constrained optimality algorithm, the orientation weight matrix and limit vector of the initial constraint model are gradually adjusted;

[0023] A stability assessment is performed on the adjusted initial constraint model. The feasibility of the modified initial constraint model under different sliding rates and tilt angles is verified through attitude simulation iterations, and the adaptive correction results are output.

[0024] Preferably, the process of establishing the constraint relationship in the guide rail direction is as follows:

[0025] Based on the adaptive correction results, a three-dimensional constraint coordinate system is established at the standardized interface position of the guide rail slot.

[0026] Spatially register the guide tongue of the expansion module with the symmetrical boss in the guide rail groove to generate a guide relationship matrix;

[0027] By monitoring the rate of change of the propulsion angle and the contact pressure signal during the insertion process, the contact imbalance area in the guide rail constraint relationship can be identified.

[0028] A fuzzy adaptive algorithm is used to dynamically adjust the contact pressure signal and establish the guide rail direction constraint relationship.

[0029] Preferably, the process of analyzing the coupling relationship between angle anomalies and pressure anomalies is as follows:

[0030] The propulsion angle signal and the contact pressure signal are synchronized and aligned along the time axis to generate an angular pressure time series dataset.

[0031] By analyzing the synchronization characteristics of angle change rate and pressure fluctuation through correlation clustering algorithm, sensitive coupling sections were identified.

[0032] An angular-pressure coupling function is constructed in the coupling-sensitive section. The function inputs are the angular deviation and pressure offset, and the output is the coupling response coefficient.

[0033] If the coupling response coefficient exceeds the set range, it is determined to be an abnormal angular compression coupling, and an abnormal coupling index is output.

[0034] Preferably, the process of determining whether the adjustment of the propulsion angle leads to a correction of the pressure distribution is as follows:

[0035] Based on the abnormal coupling index, the joint variation law of angular deviation and contact pressure recovery degree is extracted, and an angular pressure coupling reference interval is established;

[0036] The current angular deviation and pressure anomaly magnitude are calculated in real time and compared with the angular pressure coupling reference range;

[0037] When the calculation results show that the pressure recovers on its own within the reference range after angle correction, it is determined that the propulsion angle adjustment can independently correct the pressure distribution.

[0038] When the calculation results show that the pressure cannot recover on its own within the reference range, it is determined that the propulsion angle adjustment cannot independently correct the pressure distribution.

[0039] Preferably, the process of simultaneously activating the pressure adjustment strategy during the propulsion angle correction is as follows:

[0040] When the angle pressure joint correction mechanism determines that the propulsion angle adjustment cannot independently correct the pressure distribution, the control unit issues a start pressure auxiliary adjustment command to activate the pressure adjustment component and enter the pre-working state.

[0041] During the angle correction process, the target pressure adjustment curve is dynamically set according to the angle deviation and the abnormal pressure amplitude, and the restoring force of the support points on both sides of the guide rail is synchronously matched according to the angle correction rate.

[0042] Based on the contact pressure signal, closed-loop feedback adjustment is implemented on the pressure distribution in the guide rail contact area to correct the pressure output in real time.

[0043] Preferably, the process of performing adaptive propulsion stability control is as follows:

[0044] Once the propulsion angle and correction pressure are both in equilibrium, the propulsion stabilization control unit is activated.

[0045] Based on the guide rail friction coefficient, attitude angle perturbation amplitude, and installation speed, the force and speed changes during the propulsion process are calculated and adjusted in real time.

[0046] Predictive control algorithms are used to dynamically optimize propulsion speed and torque distribution. Combined with monitoring data on the temperature rise of the guide rails between the terminal body and the expansion module, the propulsion rate and contact pressure are dynamically adjusted.

[0047] The output propulsion end signal triggers the locking mechanism to complete the installation and fixation, forming an adaptive propulsion stability control.

[0048] A modular installation system for a dedicated transformer intelligent converged terminal rail includes:

[0049] Install the sensing module: Real-time detection of the installation status of the terminal body, and extraction of attitude angle and sliding direction information;

[0050] Orientation correction module: performs orientation deviation detection, calculates longitudinal and lateral attitude offsets, and adaptively corrects the initial constraint model;

[0051] Insertion constraint module: Establishes guide rail direction constraint relationship during the insertion of the expansion module, and monitors the propulsion angle and contact pressure in real time;

[0052] Angle pressure correction module: Determines whether angle adjustment can restore pressure. If the pressure cannot be restored to normal after angle adjustment, activates the pressure auxiliary adjustment strategy.

[0053] Stability control module: After the propulsion angle and contact pressure return to a balanced state, stability control is performed.

[0054] Compared with the prior art, the present invention provides a modular installation system and method for a dedicated transformer intelligent fusion terminal rail, which has the following beneficial effects:

[0055] This invention achieves multi-dimensional dynamic perception, adaptive correction of attitude offset, and real-time establishment of guide rail constraint relationships during the installation process of the intelligent fusion terminal, effectively ensuring the attitude accuracy and positional precision of the expansion module during its sliding into the terminal body. Through a joint angle and pressure correction mechanism, it couples and adjusts abnormal propulsion angles and contact pressures, enabling the simultaneous activation of a pressure adjustment strategy when angle fine-tuning alone cannot restore pressure, coordinating angle and pressure states in real time to achieve overall stability during the insertion process. The adaptive propulsion stabilization control module, combined with guide rail friction characteristics, attitude perturbations, and dynamic optimization of propulsion speed, achieves multi-parameter coordinated control of propulsion rate, contact pressure, and end-effector impact, effectively reducing risks such as offset, tilting, rebound, and localized stress concentration during installation. It ensures high-precision docking, reliable fixation, and structural safety of terminal modules in complex installation environments, while improving modular installation efficiency, reducing the need for manual intervention and repetitive adjustments, significantly enhancing the automation level and system reliability of the installation process, and providing technical support for the safe and efficient deployment of dedicated transformer intelligent fusion terminals. Attached Figure Description

[0056] Figure 1 This is a schematic diagram of the method of the present invention;

[0057] Figure 2 This is a schematic diagram of the structure of the present invention. Detailed Implementation

[0058] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] Example 1: Please refer to Figure 1 As shown in the figure, the modular installation method of the intelligent converged terminal rail for special transformers according to an embodiment of the present invention includes the following steps:

[0060] S1: Dynamically sense the installation status of the terminal body, and intelligently map the sliding direction of the terminal body based on the hierarchical limiting structure of the guide rail slot, and generate an initial constraint model of the installation direction by combining the attitude angle detection results.

[0061] The process of generating the initial constraint model for the installation direction in S1 by combining the attitude angle detection results is as follows:

[0062] Using multi-axis attitude sensors in the installation environment, the spatial position, tilt angle, yaw angle and pitch angle of the terminal body are collected synchronously;

[0063] Based on the geometric reference plane of the guide rail slot, the angle distribution between the central axis of the terminal body and the reference axis of the slot is calculated, and an attitude angle vector field is generated. In the guide rail installation structure, the geometric reference plane of the slot is defined as the reference plane of the installation direction. According to the three-dimensional geometric model of the guide rail obtained by scanning before installation, the coordinate parameters of the reference axis of the slot are extracted. The central axis parameters in the attitude data of the terminal body are transformed into three-dimensional coordinates, and the angle distribution between the central axis and the reference axis of the slot on different sections is calculated. The attitude angle change distribution matrix is ​​established by piecewise integration and spatial interpolation methods, forming a vector field describing the spatial attitude deviation of the terminal body relative to the guide rail slot. The attitude angle vector field is used to reflect the attitude change trend and the degree of angle deviation of the terminal body during the sliding into the guide rail.

[0064] A weighted fitting algorithm is used to perform multidimensional constraint fusion of the attitude angle vector field and extract the weight factors of the offset in each direction. The attitude angle vector field is input into the constraint fusion module, and the weighting coefficients are set according to the geometric constraint strength of each direction of the guide rail slot. The least squares fitting and gradient descent joint optimization algorithm is used to perform multidimensional fitting and constraint fusion of attitude offset in different directions. The algorithm iteratively calculates the offset contribution rate of each attitude component (pitch, yaw, tilt) in the spatial coordinate system, and obtains the corresponding weight factors through the normalization process. These weight factors reflect the influence intensity of attitude changes in each direction on the overall installation orientation stability.

[0065] The weighting factors are input into the initial constraint modeling unit, and the deformation estimation results of the terminal body shell and the installation space boundary conditions are combined to generate the initial constraint model of the installation direction. Based on the finite element structural parameters and the elastic modulus of the material, the distribution of small deformations of the terminal body shell under the stress installation state is estimated. The deformation estimation results and the installation space boundary conditions are input into the initial constraint modeling unit. The modeling unit constructs the direction constraint matrix and the limit condition vector according to the weighting factors, and performs linear solution and model convergence verification. The generated initial constraint model of the installation direction can completely describe the spatial attitude constraint relationship of the terminal body during the guide rail installation process.

[0066] S2: Perform directional deviation detection on the initial constraint model, combine the spatial difference between the guide protrusion in the guide rail slot and the main body attitude vector, calculate the longitudinal and lateral attitude offsets, and adaptively correct the initial constraint model based on the offsets.

[0067] The process of calculating the longitudinal and lateral attitude offsets in S2 is as follows:

[0068] The attitude angle information of the terminal body in the guide rail slot coordinate system is extracted from the initial constraint model, and a mapping function between lateral and longitudinal offset is established. The attitude angle data in the initial constraint model is mapped to the coordinate system of the guide rail slot, including the spatial reference axes of the longitudinal sliding direction and the lateral direction. By analyzing the deviation angle of the central axis of the terminal body relative to the slot reference axis, a mathematical mapping relationship between longitudinal and lateral offset is established. The mapping function uses a three-dimensional rotation matrix or Euler angle transformation method to accurately convert the attitude angle change into lateral and longitudinal displacement.

[0069] Real-time offset data during the sliding process is collected by micro-displacement sensors deployed on both sides of the guide rail and compared with the attitude angle prediction trajectory. High-precision micro-displacement sensors (such as capacitive displacement sensors or laser displacement sensors) are deployed on both sides of the guide rail to collect the minute displacement changes of the terminal body during the sliding process in real time, including longitudinal sliding offset, lateral deviation and minute vibration. The collected displacement data is compared with the attitude angle trajectory predicted in the initial constraint model in real time. By calculating the difference between the actual offset and the predicted offset, the possible attitude deviation during the sliding process can be determined.

[0070] A bidirectional differential compensation algorithm is used to eliminate sensor drift error and obtain the corrected real-time offset. The bidirectional differential compensation algorithm is applied to the displacement data collected by the sensor, that is, the displacement is collected in the forward direction of sliding in and the reverse direction of micro retraction, and the sensor zero-point drift, temperature drift and installation micro error are eliminated by calculating the bidirectional average deviation. The high-frequency noise is smoothed by combining a low-pass filter or Kalman filter algorithm, so as to obtain stable and reliable real-time lateral and longitudinal offset.

[0071] Based on the hierarchical characteristics of the guide rail slot limit boundary, the joint offset vector of longitudinal and lateral offset is calculated, and the attitude offset is output. The lateral and longitudinal offsets are mapped to the hierarchical limit coordinate system of the guide rail slot. Combined with the constraint strength and priority of each limit segment, the joint offset vector of longitudinal and lateral offset is calculated. The joint offset vector can simultaneously quantify the longitudinal sliding deviation and the degree of lateral deviation. Combined with the attitude angle weight factor and guide rail boundary conditions, the offset direction and magnitude are comprehensively evaluated. The output attitude offset is used for adaptive constraint model correction to ensure that the attitude of the terminal body remains within a controllable range during the sliding process.

[0072] The process of adaptively correcting the initial constraint model based on the offset in S2 is as follows:

[0073] By combining the attitude offset with the real-time pressure distribution at the guide rail contact point and the deformation state of the groove, the position adjustment parameters of the constraint surface are dynamically calculated. The longitudinal and lateral attitude offsets are obtained and combined with the real-time pressure distribution at the contact point and the small deformation state of the guide rail groove during the sliding process to establish a multi-dimensional constraint surface mapping relationship. By analyzing the influence of the non-uniformity of the pressure distribution and the elastic deformation of the groove on the attitude of the terminal body, the position adjustment parameters of each constraint surface in space are dynamically calculated, so that the constraint model can reflect the actual mechanical contact conditions.

[0074] A constraint optimization algorithm based on gradient descent is used to progressively adjust the orientation weight matrix and limit vector of the initial constraint model. The calculated constraint surface position adjustment parameters are input into the constraint optimization algorithm unit, and the initial constraint model is iteratively optimized through the gradient descent method. The algorithm progressively adjusts the orientation weight matrix to optimize the constraint response of the terminal body in the longitudinal sliding and lateral deviation directions, while modifying the limit vector to match the slot graded limit characteristics. During the iteration process, the constraint deviation and convergence error are evaluated in real time to ensure that the modified model approaches the optimal constraint state in each direction.

[0075] A stability assessment is performed on the adjusted initial constraint model. The feasibility of the modified initial constraint model under different sliding rates and tilt angles is verified through attitude simulation iterations, and adaptive correction results are output. The modified constraint model is then subjected to attitude simulation iterations in a simulation environment to simulate the motion trajectory and attitude changes of the terminal body under different sliding rates, tilt angles, and perturbation conditions. By comparing the error between the actual offset and the model's predicted offset, the stability and feasibility of the model under various operating conditions are evaluated. If the simulation verification passes, the reliability of the adaptive correction results can be confirmed, and these results can be used as input parameters for subsequent guide rail insertion direction deviation correction, achieving safe and precise installation of the terminal body.

[0076] S3: Push the expansion module into the standardized interface of the terminal body along the guide rail direction. Utilize the symmetrical guiding structure of the interface and the differentiated distribution of contact points to establish a constraint relationship in the guide rail direction, and monitor the pushing angle and contact pressure in real time during the insertion process.

[0077] The process of establishing the constraint relationship of the guide rail direction in S3 is as follows:

[0078] Based on the adaptive correction results, a three-dimensional constraint coordinate system is established at the standardized interface position of the guide rail slot. The constraint model results after the previous adaptive correction are obtained, and the three-dimensional constraint coordinate system of the terminal body is defined with the standardized interface of the guide rail slot as the reference. It covers the longitudinal sliding direction, the lateral position and the vertical height direction, so that the subsequent insertion operation can be carried out under a unified spatial reference. By aligning the origin of the coordinate system with the geometric center of the guide rail, it can be ensured that all spatial measurements and constraint calculations have a clear spatial reference.

[0079] The guide tongue of the expansion module is spatially registered with the symmetrical boss in the guide rail groove to generate a guide relationship matrix; the pre-set guide tongue on the expansion module is three-dimensionally registered with the symmetrical boss in the guide rail groove, and a guide relationship matrix is ​​generated by a geometric matching algorithm. The matrix describes in detail the relative position, tilt angle, contact point and gap distribution between the tongue and the boss, which is used to accurately express the constraint relationship of the expansion module along the guide rail direction. The matrix can quantify the guide accuracy of the tongue inserted into the guide rail groove.

[0080] By monitoring the rate of change of the propulsion angle and the contact pressure signal during the insertion process, the contact imbalance area in the guide rail constraint relationship is identified; real-time angle and pressure sensors are used to monitor the rate of change of the insertion angle of the expansion module into the guide rail and the pressure distribution at each contact point. By analyzing the dynamic deviation of the propulsion angle and the contact pressure, the contact imbalance area in the guide rail directional constraint relationship is identified, such as excessive pressure on one side or local angle deviation. The identification process can provide target area information for subsequent dynamic adjustment, ensuring that the constraint relationship remains balanced and reliable throughout the entire sliding process.

[0081] A fuzzy adaptive algorithm is used to dynamically adjust the contact pressure signal and establish a guide rail directional constraint relationship. The pressure signal of the identified contact imbalance area is input into the fuzzy adaptive control algorithm. By dynamically adjusting the force distribution of the support points on both sides of the guide rail, pressure equalization is achieved. The algorithm continuously corrects the guiding relationship based on real-time angle and pressure feedback, optimizes the constraint direction and contact state of the guide rail on the expansion module, and finally establishes a stable and repeatable guide rail directional constraint relationship. This ensures the synchronous coordination of the guide rail sliding path and the contact force distribution, and improves the accuracy and safety of the terminal modular installation.

[0082] S4: When the propulsion angle deviates from the preset range and is accompanied by abnormal changes in contact pressure, the angle and pressure joint correction mechanism is activated to analyze the coupling relationship between the abnormal angle and the abnormal pressure, and to determine whether the adjustment of the propulsion angle will lead to the correction of the pressure distribution. If the pressure cannot be restored to normal after the angle adjustment, the pressure auxiliary adjustment strategy will be activated simultaneously during the propulsion angle correction process.

[0083] The process of analyzing the coupling relationship between angle anomalies and pressure anomalies in S4 is as follows:

[0084] The propulsion angle signal and contact pressure signal are synchronized and aligned along the time axis to generate an angle pressure time series dataset. Propulsion angle and contact pressure data are simultaneously collected by a three-axis attitude sensor installed on the main body of the terminal and a multi-point pressure sensor at the guide rail interface. During the acquisition process, the angle signal is transformed by a rotation matrix to map the pitch angle, yaw angle and roll angle to the guide rail slot coordinate system. The pressure signal is normalized according to the corresponding contact point position. Through linear interpolation and timestamp alignment methods, the two types of signals are mapped to a unified time series to form an angle pressure time series dataset. Each time point includes the angle deviation, lateral offset and corresponding contact pressure value to ensure that transient fluctuations and high-frequency disturbance characteristics are preserved throughout the sliding process.

[0085] By analyzing the synchronization characteristics of angle change rate and pressure fluctuation through correlation clustering algorithm, coupling sensitive sections are identified. Local windowing is performed on the angle pressure time series data. Within each sliding window, the instantaneous change rate of angle deviation and the standard deviation of contact pressure offset are calculated. The Pearson correlation coefficient method is used to evaluate the synchronization between the two. High correlation coefficient windows are clustered to form a set of coupling sensitive sections. The influence of graded limit of guide rail groove, guide boss position and weight distribution of expansion module on pressure response is considered, so that the identified sensitive sections accurately reflect the key time period when angle abnormality may cause pressure abnormality.

[0086] An angular-pressure coupling function is constructed in the coupling-sensitive section. The function takes angle deviation and pressure offset as inputs and outputs the coupling response coefficient. Historical experimental data and real-time measurement data are collected within the coupling-sensitive section to establish the correspondence between angle changes and pressure response. By analyzing the continuous variation of angle deviation and pressure offset within the sensitive section, the coupling trend and sensitivity are extracted. The model can quantify the range of pressure anomalies that may be caused by angle anomalies, providing a basis for judging whether angle adjustment can naturally restore pressure.

[0087] If the coupling response coefficient exceeds the set range, it is determined to be an abnormal angular pressure coupling, and an abnormal coupling index is output. The sensitivity output by the coupling relationship model is compared with the preset abnormal threshold. When the angular pressure coupling strength exceeds the threshold, it is determined to be an abnormal coupling state, and an abnormal coupling index is generated, including the time of abnormal occurrence, the position of the affected guide rail contact point, the amount of angular deviation, the amount of pressure offset, and the coupling sensitivity level. This index is transmitted to the angular pressure joint correction module in real time to trigger the pressure auxiliary adjustment strategy and the angle fine adjustment operation, so as to ensure that the abnormality in the insertion process can be controlled and corrected in a timely and accurate manner.

[0088] The process in S4 for determining whether the thrust angle adjustment involves correction of the pressure distribution is as follows:

[0089] Based on the abnormal coupling index, the joint variation law of angle deviation and contact pressure recovery degree is extracted to establish an angle-pressure coupling reference interval. Historical installation sample data is systematically collected, including the curves of angle deviation and contact pressure change under different propulsion speeds, guide rail slot size deviations, expansion module geometric characteristics, and environmental temperature and humidity conditions. Through statistical analysis of historical samples, the joint variation pattern of angle deviation and pressure recovery amplitude is extracted. Combined with the graded limiting structure of the guide rail slot and the layout of interface support points, the angle-pressure coupling relationship is mapped into a reference interval. The reference interval not only includes the upper and lower limits of the pressure recovery after angle correction, but also marks the pressure fluctuation trend under different deviation rates.

[0090] The current angular deviation and pressure anomaly amplitude are calculated in real time and compared with the angular-pressure coupling reference range. At the same time, the terminal body angular deviation output by the multi-axis attitude sensor and the pressure distribution data collected by the pressure sensors deployed at the guide rail slot and the contact point of the expansion module are collected. All real-time collected signals are processed synchronously through timestamps and mapped to a unified guide rail coordinate system so as to directly perform corresponding analysis with the angular-pressure coupling reference range. During the acquisition process, the propulsion speed, module insertion force and guide rail slot micro-deformation state are also recorded.

[0091] When the calculation results show that the pressure recovers on its own within the reference range after angle correction, it is determined that the propulsion angle adjustment can independently correct the pressure distribution. The real-time collected angle deviation and pressure anomaly amplitude are matched with the reference range. By comparing whether the pressure naturally falls into the reference range after angle correction, it is determined whether the pressure can recover on its own by angle adjustment. If the pressure recovery value is within the reference range, a reliability analysis is further conducted by combining the guide rail limit position, the insertion depth of the expansion module, and the distribution of contact points to ensure that the judgment is not based on a single pressure value, but on a comprehensive consideration of the dynamic effect of angle adjustment and structural constraints, thereby determining that the propulsion angle adjustment can independently correct the pressure distribution.

[0092] When the calculation results show that the pressure cannot recover on its own within the reference range, it is determined that the propulsion angle adjustment cannot independently correct the pressure distribution. If the real-time pressure change exceeds the reference range and cannot recover to a reasonable range after angle correction, it is determined that the propulsion angle adjustment cannot independently correct the pressure distribution. The angle-pressure joint correction mechanism automatically triggers the pressure auxiliary adjustment strategy, adjusts the elastic restoring force of the support points on both sides of the guide rail in real time, dynamically distributes the contact pressure, and ensures that the pressure is evenly distributed along the entire guide rail contact surface through closed-loop feedback control.

[0093] The process of simultaneously activating the pressure adjustment strategy during the propulsion angle correction in S4 is as follows:

[0094] When the angle-pressure joint correction mechanism determines that the propulsion angle adjustment cannot independently correct the pressure distribution, the control unit issues a pressure auxiliary adjustment start command to activate the pressure adjustment component and put it into a standby working state. When the angle-pressure joint correction mechanism determines that the propulsion angle adjustment cannot independently correct the pressure distribution, the system control unit immediately issues a pressure auxiliary adjustment start command to put the pressure adjustment component into a standby working state, including starting the hydraulic or elastic adjustment mechanism, activating the pressure sensor and data acquisition unit, and initializing the closed-loop control parameters. By preparing the pressure adjustment path and sensor feedback mechanism in advance, it ensures that the pressure abnormality can be responded to synchronously during the angle fine adjustment process, and prevents local pressure overload or uneven guide rail contact.

[0095] During the angle correction process, a target pressure adjustment curve is dynamically set based on the angle deviation and the magnitude of the pressure anomaly, and the restoring force of the support points on both sides of the guide rail is synchronously matched according to the angle correction rate. Based on the real-time collected angle deviation and contact pressure anomaly magnitude, the distribution characteristics of the current pressure anomaly are calculated, and a target pressure adjustment curve is dynamically generated. The target curve is distributed to the elastic restoring force of the support points on both sides of the guide rail in a way that matches the angle correction rate, so as to achieve uniform pressure change along the guide rail contact surface. The whole process takes into account the module insertion depth, guide rail slot deformation, support point geometric distribution, and pressure adjustment experience of historical installation samples to achieve the synchronicity and continuity of pressure adjustment.

[0096] Based on the contact pressure signal, closed-loop feedback adjustment is implemented to regulate the pressure distribution in the guide rail contact area, and the pressure output is corrected in real time. The contact pressure signal is collected in real time by pressure sensors distributed in the guide rail contact area, and the collected data is input into the closed-loop control unit for dynamic calculation. The control unit compares the real-time pressure value with the target pressure adjustment curve and corrects the restoring force of each support point in real time to ensure that the pressure output is continuous and stable along the guide rail contact surface, avoiding local overpressure or pressure rebound. Through multi-channel redundant sensing and adaptive feedback algorithm, abnormalities can be monitored and corrected in real time during angle adjustment and pressure adjustment, so as to achieve overall stability and safety of the insertion process.

[0097] S5: After the propulsion angle and contact pressure have returned to equilibrium, adaptive propulsion stabilization control is executed.

[0098] The process of performing adaptive propulsion stability control in S5 is as follows:

[0099] After the propulsion angle and correction pressure reach a balance, the propulsion stabilization control unit is activated. The activation process includes initializing various sensor data acquisition modules, such as angle sensors, pressure sensors, and temperature sensors, while activating the actuator interface and placing the propulsion motor or micro-stepping drive device into standby mode. Through pre-calibrated control parameters and real-time data channels, it is ensured that it can immediately and effectively respond to minor disturbances and deviations during the propulsion process after activation.

[0100] Based on the guide rail friction coefficient, attitude angle perturbation amplitude, and installation speed, the system performs real-time calculation and adjustment of force and speed changes during the propulsion process. During propulsion, the system combines the guide rail friction coefficient, attitude angle perturbation amplitude of the terminal body, and current installation speed to calculate the module's force changes and propulsion speed fluctuations in real time. Through the built-in control algorithm, the system fuses and analyzes the data collected by various sensors, including parameters such as guide rail contact pressure, lateral offset, and tilt, to determine the resistance or sliding anomalies that may occur during propulsion. Based on the calculation results, the system dynamically adjusts the propulsion speed and torque to ensure that the extension module experiences uniform force and stable attitude during the slide-in process along the guide rail, preventing impact, tilting, or rebound.

[0101] Predictive control algorithms are employed to dynamically optimize the propulsion speed and torque distribution. By combining the temperature rise monitoring data of the guide rail contact between the terminal body and the expansion module, the propulsion rate and contact pressure are dynamically adjusted. By combining the temperature rise monitoring data of the guide rail contact between the terminal body and the expansion module, the frictional heating or local pressure anomalies that may occur during the propulsion process are predicted, and the propulsion rate and contact pressure are dynamically adjusted according to the prediction results. This achieves coordinated distribution of speed and force, ensuring that the insertion process remains stable under different sliding rates, different friction conditions, and different ambient temperatures, avoiding the impact caused by excessively fast propulsion or the time wasted by excessively slow propulsion.

[0102] The system outputs a propulsion end signal and triggers the locking mechanism to complete the installation and fixation, forming an adaptive propulsion stability control. When the propulsion process is completed and the terminal body and the expansion module reach the design position, the system outputs a propulsion end signal and triggers the locking mechanism to fix the module in the guide rail slot. During the locking process, the torque sensor monitors the contact state of the guide rail to ensure that the locking action and the guide rail constraint relationship are accurately matched, avoiding loosening or secondary adjustment requirements, forming a complete adaptive propulsion stability control closed loop, and achieving high reliability and safety in the modular installation process.

[0103] Example 2: As Figure 2 As shown, a modular installation system for a dedicated transformer intelligent converged terminal rail includes:

[0104] Install the sensing module: Real-time detection of the installation status of the terminal body, and extraction of attitude angle and sliding direction information;

[0105] Orientation correction module: performs orientation deviation detection, calculates longitudinal and lateral attitude offsets, and adaptively corrects the initial constraint model;

[0106] Insertion constraint module: Establishes guide rail direction constraint relationship during the insertion of the expansion module, and monitors the propulsion angle and contact pressure in real time;

[0107] Angle pressure correction module: Determines whether angle adjustment can restore pressure. If the pressure cannot be restored to normal after angle adjustment, activates the pressure auxiliary adjustment strategy.

[0108] Stability control module: After the propulsion angle and contact pressure return to a balanced state, stability control is performed.

[0109] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0110] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for installing a special intelligent fusion terminal guide rail modularization, characterized in that, The method comprises the following steps: The installation state of the terminal body is dynamically perceived, and the sliding direction of the terminal body is intelligently mapped based on the hierarchical limiting structure of the guide rail slot, and an initial constraint model of the installation direction is generated in combination with the attitude angle detection result; The process of generating the initial constraint model of the installation direction in combination with the attitude angle detection result is: The spatial position, inclination angle, yaw angle and pitch angle of the terminal body are synchronously collected by using a multi-axis attitude sensor in the installation environment; Based on the geometric reference surface of the guide rail slot, the included angle distribution between the central axis of the terminal body and the reference axis of the slot is calculated, and an attitude angle vector field is generated; A weighted fitting algorithm is used to perform multi-dimensional constraint fusion on the attitude angle vector field, and weight factors of the lateral deviation and the longitudinal deviation are extracted; The weight factors are input into an initial constraint modeling unit, and an initial constraint model of the installation direction is generated in combination with the deformation amount estimation result of the terminal body shell and the installation space boundary condition; Direction deviation detection is performed on the initial constraint model, the spatial difference between the guide protrusion in the guide rail slot and the body attitude vector is calculated, and the longitudinal and lateral attitude deviations are calculated, and the initial constraint model is adaptively corrected according to the deviations; The process of calculating the longitudinal and lateral attitude deviations is: The attitude angle data of the terminal body in the guide rail slot coordinate system is extracted from the initial constraint model, a mapping function of the lateral deviation and the longitudinal deviation is established, the attitude angle data in the initial constraint model is mapped to the coordinate system of the guide rail slot, including the spatial reference axes of the longitudinal sliding direction and the lateral direction, the mathematical mapping relationship between the longitudinal deviation and the lateral deviation is established by analyzing the deviation angle of the central axis of the terminal body relative to the reference axis of the slot; Real-time deviation data in the sliding process is collected by the micro-displacement sensors arranged on both sides of the guide rail, and is compared with the attitude angle prediction track; A two-way difference compensation algorithm is used to eliminate the sensor drift error, and the corrected real-time deviation is obtained; According to the hierarchical characteristics of the limiting boundary of the guide rail slot, the joint deviation vector of the lateral deviation and the longitudinal deviation is calculated, and the attitude deviation is output; The extension module is pushed into the standardized interface of the terminal body along the guide rail direction, the constraint relationship in the guide rail direction is established by using the symmetrical guide structure of the interface and the differential distribution of the contact contact points, and the pushing angle and the contact pressure are monitored in real time during the plug-in process; When it is detected that the pushing angle deviates from the preset range and the contact pressure abnormally changes, the angle-pressure joint correction mechanism is started, the coupling relationship between the angle abnormality and the pressure abnormality is analyzed, it is judged whether the pushing angle adjustment is accompanied by correction of the pressure distribution, and if the pressure cannot be restored to normal after the pushing angle adjustment, the pressure auxiliary adjustment strategy is started synchronously in the pushing angle correction process; After the pushing angle and the contact pressure are both returned to the balanced state, adaptive pushing stable control is performed.

2. The method of claim 1, wherein the method further comprises: The process of adaptively correcting the initial constraint model according to the deviation is: The attitude deviation is combined with the real-time guide rail contact point pressure distribution and the slot deformation state to dynamically calculate the constraint surface position adjustment parameter; The constraint optimal algorithm based on gradient descent is used to gradually adjust the direction weight matrix and the limiting vector of the initial constraint model. Performing stability evaluation on the adjusted initial constraint model, verifying the feasibility of the modified initial constraint model at different sliding-in speeds and inclination angles through attitude simulation iteration, and outputting adaptive correction results.

3. The method of claim 2, wherein the method further comprises: The process of establishing the constraint relationship in the guide rail direction is as follows: According to the adaptive correction results, a three-dimensional constraint coordinate system is established at the standardized interface position of the guide rail slot; Space registration is performed between the guide tongue of the extension module and the symmetrical boss in the guide rail slot to generate a guide relationship matrix; By monitoring the change rate of the advancing angle and the contact pressure signal during the insertion process, the uneven contact area in the guide rail constraint relationship is identified; A fuzzy adaptive algorithm is used to dynamically adjust the contact pressure signal to establish the guide rail direction constraint relationship.

4. The method of claim 3, wherein the method further comprises: The process of analyzing the coupling relationship between angle abnormalities and pressure abnormalities is as follows: Synchronize the advancing angle signal and the contact pressure signal along the time axis to generate an angle-pressure time series dataset; By using a correlation clustering algorithm, the synchronization characteristics of the angle change rate and the pressure fluctuation are analyzed to identify the coupling sensitive section; An angle-pressure coupling function is constructed in the coupling sensitive section, with the angle deviation and the pressure deviation as inputs and the coupling response coefficient as output. If the coupling response coefficient exceeds the set range, it is determined that there is an angle-pressure abnormal coupling, and an abnormal coupling index is output.

5. The method of claim 4, wherein the method further comprises: The process of determining whether the advancing angle adjustment is accompanied by pressure distribution correction is as follows: Based on the abnormal coupling index, the joint change rule of the angle deviation and the contact pressure recovery amount is extracted to establish an angle-pressure coupling reference interval; The current angle deviation and pressure abnormal amplitude are calculated in real time and compared with the angle-pressure coupling reference interval; When the calculation result shows that the pressure recovers within the reference interval after the advancing angle correction, it is determined that the advancing angle adjustment can independently correct the pressure distribution; When the calculation result shows that the pressure cannot recover within the reference interval, it is determined that the advancing angle adjustment cannot independently correct the pressure distribution.

6. The method of claim 5, wherein the method further comprises: The process of synchronously starting the pressure auxiliary adjustment strategy during the advancing angle correction process is as follows: When the angle-pressure joint correction mechanism determines that the advancing angle adjustment cannot independently correct the pressure distribution, the control unit sends a start pressure auxiliary adjustment instruction to activate the pressure adjustment component to enter a standby state; During the advancing angle correction execution process, the target pressure adjustment curve is dynamically set according to the angle deviation and the pressure abnormal amplitude, and the restoring force of the support points on both sides of the guide rail is matched at the same angle correction rate; Based on the contact pressure signal, closed-loop feedback adjustment is performed on the pressure distribution of the guide rail contact area to correct the pressure output in real time.

7. The method of claim 6, wherein the method further comprises: The process of performing adaptive advancing stability control is as follows: After the advancing angle and the corrected pressure reach a balanced state, the advancing stability control unit is started; Based on the guide rail friction coefficient, attitude angle perturbation amplitude, and installation speed, the force and speed changes during the advancing process are calculated and adjusted in real time; A predictive control algorithm is used to dynamically optimize the advancing speed and torque distribution, and the advancing speed and contact pressure are dynamically adjusted based on the guide rail contact temperature monitoring data of the terminal main body and the extension module; An advancing end signal is output to trigger the locking mechanism to complete the installation and fixation, forming adaptive advancing stability control.

8. A dedicated intelligent fusion terminal rail modular installation system applied to the method of any one of claims 1-7, characterized in that, It includes: Installation sensing module: real-time detection of the installation state of the terminal main body, extraction of attitude angle and sliding-in direction information; Direction correction module: perform direction deviation detection, calculate longitudinal and lateral attitude offset, and adaptively correct the initial constraint model; Plug-in constraint module: establish guide rail direction constraint relationship during the extension module insertion process, and monitor the advance angle and contact pressure in real time; Angle pressure correction module: judge whether the advance angle adjustment can restore the pressure, and if the pressure cannot be restored to the normal starting pressure after the advance angle adjustment, adjust the strategy; Stable control module: execute stable control after the advance angle and contact pressure return to the balanced state.

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